extfieldsofstudy:
Biology
Computer Science
Medicine

text:
Signal duration and the time scale dependence of signal integration in biochemical pathways

Background Signal duration (e.g. the time over which an active signaling intermediate persists) is a key regulator of biological decisions in myriad contexts such as cell growth, proliferation, and developmental lineage commitments. Accompanying differences in signal duration are numerous downstream biological processes that require multiple steps of biochemical regulation. Results Here we present an analysis that investigates how simple biochemical motifs that involve multiple stages of regulation can be constructed to differentially process signals that persist at different time scales. We compute the dynamic, frequency dependent gain within these networks and resulting power spectra to better understand how biochemical networks can integrate signals at different time scales. We identify topological features of these networks that allow for different frequency dependent signal processing properties. Conclusion We show that multi-staged cascades are effective in integrating signals of long duration whereas multi-staged cascades that operate in the presence of negative feedback are effective in integrating signals of short duration. Our studies suggest principles for why signal duration in connection with multiple steps of downstream regulation is a ubiquitous motif in biochemical systems.

Background
Signal duration (e.g. the length of time over which a signaling intermediate is active) is a critical determinant in mediating cell decisions in numerous biological processes including cell growth, proliferation, and developmental lineage commitments (Fig. 1) [1][2][3][4][5][6][7][8]. One fundamental issue in signal transduction and cell decision making then is how differences in signal duration are detected to achieve the appropriate biological response.
Accompanying changes in signal duration are multiple stages of biochemical regulation of differing network topology that collectively integrate an incoming signal to deliver a specific biological response. The sequential activation of multiple steps in a biochemical pathway is a ubiquitous regulatory motif involved in many aspects of gene regulation, metabolism, and intracellular signal transduction. Many advantages of having multiple steps of regulation as opposed to having activation occur through a single step have been documented. A signaling cascade can allow for attenuation of noise, incorporation of additional regulatory checkpoints or proofreading steps, and increased tunability of the input signal [9][10][11][12]. Other studies have established conditions under which signaling cascades amplify or attenuate incoming signals [13][14][15]. These conditions are established by rates of activation, rates of deactivation that are set by phosphatase activities, and the presence of scaffold proteins [14][15][16]. However, how these features synergize with downstream effector pathways to detect differences in signal duration has not been fully studied.
A recent study has proposed a model that predicts how signals with different dynamical characteristics can be distinguished upon integration into different network architectures [17,18]. We develop a formalism to complement their approach and, as a consequence, identify general principles for how different network topologies can differentially integrate signals that persist at different time scales. We focus on a simple model of the sequential enzy-matic activation of multiple species along a pathway to understand mechanistic principles underlying how multiple stages in a biochemical pathway can integrate differences in signal duration. We use a model of a weakly activated cascade [13,14,19], whose assumptions we first motivate, to study the question of how biochemical cascades detect the time scale dependence of input signals. Our approach is similar to previous work [20] that investigated the frequency dependent signal processing properties of single enzymatic cycles. The model allows us to characterize the dynamics by obtaining exact expressions for the power spectra of linearized biochemical networks of multiple stages with arbitrary length and connectivity and we focus on how these frequency dependent signal processing properties of cascades are used to detect differences in signal duration.
Physiological examples of signal duration determining the phenotypic outcome in signal transduction Figure 1 Physiological examples of signal duration determining the phenotypic outcome in signal transduction. Four examples of physiological processes in which branching phenotypic decisions are believed to be controlled by the detection of differences in signal duration [5,6,8,[28][29][30].

Adipogenesis
Adipogenesis Proliferation We first show that biochemical cascades can function as both high low and high pass filters depending on the topology of the network architecture. A low pass filter removes high frequency (short duration) components of a signal and a high pass filter removes low frequency (long duration) components of a signal. These filtering capabilities are determined by differential positive and negative regulation within the biochemical pathway. Importantly, the filtering capabilities are determined by the presence of feedback as well as the amplification and attenuation properties at different steps in the cascade that are set by the differences in phosphatase activities at different stages along the cascade. Ultimately, our findings suggest design principles that characterize how biochemical cascades are well suited for detecting time scale dependent differences in biochemical signals.

Detection of long duration signals
In the model as previously developed [14], an input signal, f(t), activates the first member of the pathway whose activation can then activate the next member. In turn, each upstream species activates its immediate downstream target and can also be deactivated by, for example, a phosphatase. Assuming Michaelis Menten kinetics for the activation and deactivation of each species along the cascade, we can write an equation for the dynamics of the active form of the i th species x i along the cascade: where E pase is the concentration of the enzyme that deactivates species i, , are the catalytic constants of the activation and deactivation steps, , are the Michaelis constants and is the total amount species available at step i. We take , at each step to be large ( , > ) so that the kinetics of the reactions are not limited by the availability of the enzyme [21]. This assumption implies that the enzyme kinetics operate in a linear, first-order regime. Next, we assume that the cascade is weakly activated (i.e. at each stage, the total number of species is much larger than the number of active species, >> x i ). In many biologically relevant instances (e.g. the Mitogen activated protein kinase (MAPK) cascade), the neglect of saturation effects is often reasonable [22]. Further, modeling the deactivation as a first order reaction is often valid when phosphatases are in excess as is the case in many physiological scenarios [23]. Eq. 1 simplifies to a system of linear first order differential equations [14]: where the first species is activated at a rate f(t); and . This scheme is depicted in Fig. 2a.
The weakly activated cascade model has the advantage that the linearity of the equations allows for analytical tractability. Eq. 2 can be conveniently analyzed by introducing Fourier transformed variables: and F(ω) = ∫dte iωt f(t). The number of activated species at stage i becomes . The power spectrum P i (ω) ≡ |X i (ω)| 2 at the i th step can also be obtained: . After iterating at each successive stage of the n step cascade, an expression for P n (ω) as a function of the power spectrum of the input signal (S(ω) ≡ |F(ω)| 2 ) is obtained: in which a frequency dependent gain g n (ω) is defined as: g n (ω) is a transfer function that converts the input S(ω) into a response and provides a measure of the signal processing capabilities of the network. The change in the amplitude of the signal output is determined by the term and the time dependence of the output is modulated by the term.
From the formula of g n (ω), one consequence of having multiple stages is readily apparent. In the high frequency regime , for each , g n (ω) rapidly decays with increasing n (g n (ω) ~ ω -2n ). Thus, longer cascades are more efficient at filtering the high frequency components of the signal from the output. This behavior is illustrated in Fig.   2b. Fig. 2b contains plots of g n (ω) for different values of n; cascades of lengths n = 1, 2, 3, 4 are shown.
In eq. 4, the relative values of along different stages of the cascade also affects the scaling behavior of g n (ω) as ω changes as well as the overall amplitude. The change in signal amplitude at the steady state (that leads to amplification or attenuation) at step i is given by the ratio of the effective rate constants for activation and deactivation . results in signal amplification and leads to attenuation of the signal at step i [13,14]. Amplification or attenuation also leads to different time Filtering of high frequency signals − dependent behaviors of g n (ω). For example, consider an n staged cascade with rate constants such that , at frequencies ω > , g n (ω) ~ ω -2n while at frequencies > ω > , g n (ω) ~ ω -2(n-1) and so forth. Thus, at intermediate frequencies, a time scale separation (as determined by different deactivation rates along the cascade), along with signal amplification and attenuation, also leads to different frequency dependent behaviors of g n (ω).
Also, from the plots in Fig. 2c (and inspection of eq. 4), it is observed that incorporation of faster steps along the cascade influences the frequency dependence of g n (ω) to a lesser extent than would be the case when the kinetics of activation are same for each successive step. Since signal propagation in these cases is limited by the slower stages of the cascade, the faster steps are effectively removed from g n (ω). This observation suggests a principle in the ability of a biochemical pathway to filter signals of short duration: when there is a positive gradient of deactivation rates (that also leads to amplification or attenuation of signal amplitude), the time dependence of signal integration for multi staged cascades more closely resembles that of a pathway involving a single step. This effect is a result of a single dominant time scale in the pathway and provides a mechanism for regulating the amplitude of the signal output while keeping the time dependence of the output the same as that of a single-staged pathway.

Detection of short duration signals
While the sequential activation of multiple steps in a biochemical pathway allows for effective filtering of the high frequency, short duration components of a signal, often the desired signal output is regulated by feedback. We will now show with our analysis that feedback control in some instances also allows for the filtering of the low frequency, long duration components of a signal. Previous work has characterized this behavior with numerical simulations [17,18]. In these instances, signals that occur at short times can be integrated while signals with a longer duration are effectively filtered because at longer times, the negative feedback loop affects the signal output.
For instance, the signal output can be affected by a feedback loop that is initiated downstream of the output. This scenario would be the case when the signal output from a biochemical cascade activates its own positive or negative regulators. For instance, in mammalian cells, the activation of extracellular regulatory kinase (ERK) often leads to the upregulation or activation of its own phosphatases [24]. In this scenario, a signal output in the form of phosphorylated ERK (ERK is known to phosphorylate on the order of one hundred substrates) is deactivated as a result of the upregulation of phosphatases that dephosphosphorylate residues in the TxY motif whose phosphorylation is necessary for activation.
Signal output is the activity of the kinase at the m th step and feedback control to the signal output at step m is initiated at a later step (i.e. n > m) and the modified set of dynamical equations becomes: where k f is the feedback strength and sets the time scale of the feedback and . This scheme is depicted in Fig. 3a.
Another biologically important example involves a negative feedback loop that acts upon a downstream layer in the cascade. However, in the linear cascade approximation that is used in this paper (that allows for extensive mathematical analysis) such a feedback loop would simply act to effectively increase the rate of deactivation of the species involved in the layer of the cascade that is involved in the feedback interaction. A model with nonlinear negative feedback (and one that is not analytically tractable) would be required to show the effect mathematically.
After applying a Fourier transformation as before, an expression for from eq. 5, albeit now more complicated, can be obtained as a function of S(ω) in closedform: where, In the case of feedback regulation, there exists a competition between processes that are realized on multiple time scales: one for the signal to propagate along the cascade to the species involved in the signal output, and the others for the additional interactions derived from the feedback loops to propagate and interact with the species involved in the output. The competition between these effects in principle may lead to a frequency dependent optimal value of . At high frequencies as before, signal propagation is limited by the time it takes to move through the cascade and high frequency components of are filtered. Also, at low frequencies, signals can potentially be attenuated when the response is dominated by the activity of the feedback loop. If the interaction from the feedback is sufficiently strong, then the low frequency components of the signal are also filtered by the cascade. In this scenario, the frequency dependent behavior of would be non monotonic.
We illustrate these ideas through consideration of a three tiered cascade that consists of a chemical species carrying the input signal, a species conferring the signal output, and a species activated downstream to the output that provides a feedback interaction to the species conferring the signal output. In this scheme, m = 1 and n = 2, and eq. 7 is simplified and becomes: Filtering of low frequency signals

Differential detection of long and short signals by two interacting species
In the previous sections, we illustrated how long and short duration signals can be differentially detected with different network structures. Alternative schemes for detecting long and short duration signals are also possible. Consider a mechanism that illustrates the time dependence of signal transduction involving the competition of two interacting products. One product is produced in greater amounts at one time scale and the other is produced in great amounts at a different time scale. Similar schemes have been investigated in the context of MAPK signaling and have shown to have many effects on integrated signal output [17,18,24,25]. For example, in Yeast MAPK pathways, the output of one pathway (e.g. the stress-induced MAPK HOG1 pathway), can inhibit the activity of the (mating response-induced MAPK FUS3 pathway) as has been previously shown [25].
Here, we focus on the dynamics and time scale dependence of these mechanisms. Consider the following scheme depicted in Fig. 4a. In this scenario, two interacting products X and Y are produced by the same signal such as is the case of two parallel, interacting MAPK pathways. A set of two kinetic equations for species X and Y (denoted by x and y respectively) can be written as follows: γ is the strength of the negative interaction from species Y to species X. The other parameters that are introduced in this model are α 1 and α 2 , that set the strength of interaction between the signal stimulus f(t) and X and Y respectively. The constitutive degradation rate constants of X and Y are β 1 and β 2 .
We can solve eq. 12 using Fourier transformation as before. We define the following as before: P  (10) and P Y (ω) = g Y (ω)S(ω).
The frequency dependent gain for species X and Y are obtained, and Plots of g X (ω) (solid) and g Y (ω) (dashed) are considered in Fig. 4b. From Fig. 4b, the following behavior is apparent. At very high frequencies, signals from f(t) are filtered by both products X and Y. At intermediate frequencies (ω 1.0 to ω ~ 10.0) signals deriving from f(t) are integrated more efficiently by species X. Therefore, short duration signals are integrated more efficiently by species X. At low frequencies, ω < 1.0, signals originating from f(t) are integrated more efficiently by species Y. As a result, long duration signals are integrated more efficiently by species Y since at long times, X is affected by the negative interaction from Y.
This simple two species model illustrates how signal specificity can be achieved from two competing products by introducing changes in signal duration of the upstream signal. Short duration signals are more effectively integrated by one species and long duration signals are more effectively detected by the other.

Integration of signals of differing duration
In the previous sections, we considered the frequency dependent gain of different network structures. In this section, we consider an incoming signal of differing duration and observe how it is differentially processed by networks that filter signals at different time scales. First, we considered the case in which the network filters short duration (high frequency) signals (Fig. 2). Next, we considered the case (Fig. 3) in which the network filters signals of long duration (low frequency).
A convenient way to parameterize signals of differing duration, while keeping the total amount of signal ∫ f(t)dt = α fixed, is to consider the function, A model of two interacting species produced by the same signal  where Θ(t) is a Heaviside step function, τ d sets the signal duration, and α is taken to be 1 (α = 1) in the appropriate units. This form of f(t) models the behavior of a typical experimental signaling time course [4]. Plots of f(t) are shown in Fig. 5a. For this choice of signal, S(ω) is easily computed; Fig. 5b for different values of τ d ranging from = 2.0 (short duration) to = 0.1 (long duration).

S(ω) is plotted in
Figs. 5c and 5d illustrate how signals S(ω) of large ( = 0.5 dotted lines) and small ( = 2.0 dashed lines) duration are integrated by the internal gains g 3 (ω) (Fig. 5c, from eq. 4) and (Fig. 5d, from eq. 8) of these multistage cascades of differing network topologies. In Fig. 5c, the signal output P 3 (ω) (from eq. 3), upon integration by a three-tiered kinase cascade is shown. Taking Integration of differences in signal duration for i ∈ 1, 2, 3, g 3 (ω) effectively filters the short ( = 2.0) duration signal and results in an output P 3 (ω) of small magnitude at all time scales 2πω -1 in the frequency spectrum. In contrast, for the signal characterized by = 0.5, signal processing through g 3 (ω) results in a signal of larger amplitude. The ratio of amplitudes (with the superscript denoting the duration used) at the optimal frequency (ω = 0) for the two signals is ≈ 17.
In Fig. 5d, the signal output (from eq. 6), obtained from a signal output that is also affected by a downstream negative (υ = -1) feedback loop, is shown. Parameters

Discussion
Our models illustrate features of biochemical pathways that allow for the discrimination of signals that only differ in their duration. It is important to note that many important, nonlinear effects, at the expense of analytical tractability, were excised in making the linear, weakly activated cascade approximation. For example, nonlinear positive feedback is known to give rise to bistability. Also nonlinear negative feedback can lead to oscillatory behavior. These effects, however, correspond to long time, steady state behavior and the present analysis focused on transient signals of different duration and it is therefore expected that such nonlinear effects are not expected to influence the qualitative behavior of the results in this study.
In summary, we computed the frequency dependent internal gain for two classes of biochemical pathways involving multiple stages of regulation. The first model consisted of a cascade of steps and showed how changes in the number of steps as well as the amplification/attention of the signal changed the networks' ability to filter high frequency (short duration) components of a signal.
Another network consisted of a sequence of steps in the form of biochemical intermediates in which the output is connected to a downstream feedback loop or an interacting product. The gain in this network can have non monotonic behavior in which the low frequency components of the signal are also filtered at time scales commensurate with the induction of the regulatory loop. This behavior enables the network to filter out signals of long duration. The minimal topological features of these biochemical networks provide distinct and robust mechanisms for integrating signals that persist with different characteristic time scales. As different temporally regulated signals often lead to different transcriptional programs such as in NF-κB signaling [26,27], it is tempting to speculate on the role that such filtering mechanisms may have in regulating gene expression.


extfieldsofstudy: Biology Medicine

text:
Human solute carrier SLC6A14 is the β-alanine carrier

The β-alanine carrier was characterized functionally in the 1960s to 1980s at the luminal surface of the ileal mucosal wall and is a Na+- and Cl−-dependent transporter of a number of essential and non-essential cationic and dipolar amino acids including lysine, arginine and leucine. β-Alanine carrier-like function has not been demonstrated by any solute carrier transport system identified at the molecular level. A series of experiments were designed to determine whether solute carrier SLC6A14 is the molecular correlate of the intestinal β-alanine carrier, perhaps the last of the classical intestinal amino acid transport systems to be identified at the molecular level. Following expression of the human SLC6A14 transporter in Xenopus laevis oocytes, the key functional characteristics of the β-alanine carrier, identified previously in situ in ileum, were demonstrated for the first time. The transport system is both Na+ and Cl− dependent, can transport non-α-amino acids such as β-alanine with low affinity, and has a higher affinity for dipolar and cationic amino acids such as leucine and lysine. N-methylation of its substrates reduces the affinity for transport. These observations confirm the hypothesis that the SLC6A14 gene encodes the transport protein known as the β-alanine carrier which, due to its broad substrate specificity, is likely to play an important role in absorption of essential nutrients and drugs in the distal regions of the human gastrointestinal tract.

Amino acids are required for many fundamental biological functions such as protein synthesis, neurotransmission, nitrogen metabolism, and cell growth. In humans and mammals the requirements for most amino acids are met by assimilation from diet. Transepithelial amino acid absorption across the intestinal wall is mediated by a number of amino acid transporters arranged in series and parallel at the luminal and serosal membranes of the intestinal epithelium . Although amino acid transporters vary in substrate selectivity, ion dependency and substrate affinity, the attribution of function to any particular transport system in intact tissues is often hampered by overlapping substrate specificity. One such amino acid transport system was described at the mucosal surface of rabbit ileum and named the β-alanine carrier (Munck & Schultz, 1969;Paterson et al. 1981;Munck, 1985;Anderson & Munck, 1987). This carrier system transports a range of both essential and non-essential amino acids and accepts non-α-amino acids such as β-alanine but has a higher affinity for dipolar (e.g. leucine) and cationic (e.g. lysine) amino acids; is Na + and Cl − dependent; is only moderately stereospecific; and has a much lower affinity for the N -methylated derivatives of its dipolar amino acid substrates (Munck, 1985;Munck & Munck, 1990, 1992a,b, 1995. The β-alanine carrier is unusual in that, under normal circumstances, its small intestinal expression is limited to the ileum (Munck & Munck, 1992a,b).
The cloning of transporter related genes over recent years has allowed molecular identification of most of the 'classical' amino acid transport systems characterized functionally in specific cells and tissues during the 1960s to 1980s. The purpose of this investigation was to establish the molecular identity of the β-alanine carrier. The solute carrier SLC6A14 has been cloned from human mammary gland, mouse colon and rat lung (Sloan & Mager, 1999;Hatanaka et al. 2001;Nakanishi et al. 2001;Ugawa et al. 2001;Umapathy et al. 2004). SLC6A14 is the 14th member of solute carrier family 6, a family of Na + -and Cl − -dependent solute transport systems many of which are involved in transmembrane movement of neurotransmitters (Chen et al. 2004). SLC6A14 (also named ATB 0,+ ) functions as a dipolar and cationic amino acid transporter with characteristics similar to J Physiol 586.17 system B 0,+ (identified originally in mouse blastocysts; Van Winkle et al. 1985). Thus far, β-alanine carrier-like function has not been demonstrated by any solute carrier transport system identified at the molecular level. In this investigation, a series of experiments were designed to determine whether SLC6A14 is the molecular correlate of the intestinal β-alanine carrier, perhaps the last of the classical intestinal amino acid transport systems to be identified at the molecular level.

Functional expression in Xenopus laevis oocytes
Human SLC6A14 cRNA was produced by in vitro transcription (using mMessage mMachine T7 Ultra kit (Ambion)) of pSPORT1 plasmid containing the SLC6A14 sequence isolated originally from MCF-7 cells . Female Xenopus laevis were killed humanely by cervical dislocation following Schedule 1 procedures. Oocytes were prepared and injected with 50 nl cRNA (1 mg ml −1 ) or water, as previously described (Kennedy et al. 2002(Kennedy et al. , 2005, and incubated at 18 • C in Barth's solution until required.

Uptake of radiolabelled amino acids
Uptake of radiolabelled amino acids (2-5 μCi ml −1 ) was measured in oocytes 2-5 days after injection, as previously described (Kennedy et al. 2002). Oocytes were washed in a NaCl-containing pH 7.4 solution (100 mM NaCl, 2 mM KCl, 1 mM CaCl 2 , 1 mM MgCl 2 , 10 mM Hepes adjusted to pH 7.4 with Tris base) and uptake measured at 22 • C for 40 min. Uptake measurements were performed in this NaCl-containing pH 7.4 solution or using a solution adjusted as follows: for the Na + -free solution, NaCl was replaced with choline chloride; for the Cl − -free solution, NaCl, KCl, CaCl 2 and MgCl 2 were replaced with sodium gluconate, potassium gluconate, calcium gluconate and MgSO 4 , respectively; for the pH 5.5 solution, Hepes was replaced by Mes. After uptake, oocytes were washed three times in ice-cold buffer and lysed in 10% SDS. Radioactivity was measured by scintillation counting.

Two-electrode voltage clamp
Oocytes (2-8 days post-injection) were superfused in an open chamber with a NaCl-containing pH 7.4 solution (see above). Oocytes were clamped at −60 mV and exposed to various concentrations of β-alanine (0.2-20 mM, 2min) or different amino acids (all at 20 mM, 2min) to allow amino acid-induced currents to be measured using a Geneclamp 500 amplifier, Digidata 1200 (Axon Instruments) and Clampex software (Kennedy et al. 2005). Currents were analysed using Clampfit 8.2. To determine the current evoked by a 2 min exposure to an amino acid, the current measured over the last 15 s of the 2 min exposure was averaged. The baseline current (taken as the average current over the 15 s before exposure to the amino acid) was then subtracted to determine SLC6A14-specific current.

Statistics
Data are means ± S.E.M. Statistical comparisons were made using ANOVA and Tukey's post hoc test using GraphPad Prism 4 (GraphPad Software Inc., San Diego, CA, USA). Curves were fitted with GraphPad Prism 4.
SLC6A14-mediated β-alanine/Na + /Cl − cotransport is a rheogenic process which generates inward current under two-electrode voltage-clamp conditions (Figs 3 and 4) consistent with a stoichiometry of 2-3 Na + : 1 Cl − : 1 amino acid, as suggested previously with other substrates for SLC6A14 (Sloan & Mager, 1999). The relative low affinity of SLC6A14 for β-alanine (K m = 2.1 ± 0.9 mM, Fig. 3), compared to leucine and lysine, is consistent with earlier observations of the β-alanine carrier in rabbit ileum (K m = 2 mM) (Munck, 1985;Munck & Munck, 1992a). At saturating substrate concentrations (20 mM), β-alanine transport via SLC6A14 is associated with a large inward current of similar magnitude (P > 0.05) to that observed with the other dipolar substrate leucine (Fig. 4). The cationic amino acid lysine was associated with a larger current (P < 0.01, lysine versus β-alanine) which raises the possibility that a component of the current is carried by the positively charged amino acid (Fig. 4). MeAIB, which is excluded from the β-alanine carrier, failed to induce significant current (P > 0.05) in the SLC6A14-injected oocytes (Fig. 4). None of the three β-alanine carrier substrates induced inward current in water-injected oocytes (Fig. 4A). The higher affinity of SLC6A14 for lysine and leucine compared to β-alanine is confirmed by the greater inhibition of [ 3 H]β-alanine uptake observed (Fig. 5) when all competing cold substrates were present at a concentration (2 mM) around the K m for β-alanine (leucine and lysine both P < 0.001 versus cold β-alanine; β-alanine P < 0.001 versus control).

Discussion
The key functional characteristics of the β-alanine carrier, as previously described only in situ in rabbit ileum (Munck, 1985), are demonstrated following expression of the SLC6A14 transporter in Xenopus laevis oocytes (Figs 1-6). The transport system is both Na + and Cl − dependent, can transport non-α-amino acids such as β-alanine with low affinity, and has a higher affinity for dipolar and cationic amino acids such as leucine and lysine (Figs 1-5). N -methylation of the substrates leucine, glycine, alanine and AIB reduces the affinity for transport (Fig. 6). In addition, the characteristic of weak stereoselectivity has been demonstrated previously with the identification of D-serine transport via SLC6A14 (Hatanaka et al. 2002). These observations confirm the hypothesis that the SLC6A14 gene encodes the transport protein known as the β-alanine carrier (Munck, 1985;Anderson & Munck, 1987). The β-alanine carrier is considered to be the Na + -dependent transporter of leucine, lysine and alanine observed originally in rabbit ileum by Munck & Schultz (1969) and Paterson et al. (1981). Importantly, these observations also indicate that the studies of the β-alanine carrier in the 1960s to 1980s can now be considered to represent in situ measurements of SLC6A14 function in the intestine.
The tissue distribution of the β-alanine carrier is unusual as the only intestinal location where function has been described is at the luminal surface of the ileum (Munck, 1985;Anderson & Munck, 1987;Munck & Munck, 1990, 1992a,b, 1995. This predominantly distal intestinal expression pattern is supported by observations using mouse gastrointestinal tract that demonstrate greater expression of SLC6A14 mRNA in the ileum and colon compared to duodenum and jejunum (Hatanaka et al. , 2002Ugawa et al. 2001;Sloan et al. 2003). In the rabbit, the physiological role of the β-alanine carrier seems certain to lie in nutrient absorption from the diet as the ileum is the site of maximal amino acid absorption in rabbit small intestine (Munck & Munck, 1992b). The physiological role in the human intestine is not known but the broad substrate specificity of SLC6A14 means that this distal intestinal site of absorption could be important in both nutrient and drug absorption. β-Alanine is a non-proteinogenic amino acid and is a component of the dipeptide carnosine (β-alanine-L-histidine), found at high concentrations in both vertebrate and non-vertebrate skeletal muscle. In humans, dietary supplementation with β-alanine (at concentrations relevant to diet) leads to an increase in skeletal muscle carnosine (Harris et al. 2006) which is associated with an improvement in performance during exercise, proposed to be due to the enhanced pH buffering effect of carnosine (Harris et al. 2006;Stout et al. 2007;Zoeller et al. 2007). In addition to cationic and dipolar amino acids, SLC6A14 transports carnitine, a range of nitric oxide synthase inhibitors, and the antiviral prodrugs valacyclovir and valganciclovir (Hatanaka et al. , 2004Nakanishi et al. 2001;Umapathy et al. 2004). Thus, SLC6A14 has great potential as a target for drug delivery programmes using slow release formulations or rectal suppositories. In addition, the colonic expression may have relevance for the absorption of bacterially derived D-amino acids as D-serine is transported by SLC6A14 (Hatanaka et al. 2002). Interestingly, the distribution pattern of SLC6A14 parallels the regions of the gastrointestinal tract that are generally colonized by bacteria. The hypothesis that SLC6A14 expression might be up-regulated following bacterial colonization is consistent with the recent demonstration of selective up-regulation of SLC6A14 mRNA and protein expression in acute cholera patients compared to convalescence such that SLC6A14 protein has been immunolocalized to the luminal surface of the human duodenum during acute infection (Flach et al. 2007). After induction, e.g. following infection with cholera, SLC6A14 could provide a highly concentrating mechanism (due to its Na + and Cl − dependence) for absorption of essential amino acids such as lysine and leucine that could otherwise be lost during excess intestinal fluid and electrolyte secretion. The SLC6A14 gene seems highly regulated being associated with obesity (Suviolahti et al. 2003;Durand et al. 2004), and being up-regulated in colorectal cancer (Gupta et al. 2005), cervical cancer , and ulcerative colitis (Flach et al. 2006). J Physiol 586.17 In summary, this study describes the first demonstration of β-alanine carrier-like function by any cloned transporter. The functional characteristics described here, which are identical to those determined by measurement of amino acid uptake across the luminal surface of flat sheets of rabbit ileal mucosa (Munck, 1985;Munck & Munck, 1990, 1992a,b, 1994, 1995, can account for all β-alanine carrier-like function and emphasize the added value of in situ measurements of physiological function over theoretical predictions of transport protein function based solely upon measurements of mRNA distribution. SLC6A14 was isolated originally from human mammary gland (Sloan & Mager, 1999) and named ATB 0,+ due to its similarity in function to the amino acid transport system B 0,+ , described in mouse blastocysts (Van Winkle et al. 1985). The observations reported in this study demonstrate that SLC6A14 is the β-alanine carrier and that the blastocyst ATB 0,+ and intestinal β-alanine carrier are one and the same transport system (Munck & Munck, 1995). The term β-alanine carrier is somewhat inappropriate as a means of identification of this intestinal transport system as it has a low affinity for β-alanine, and the intestinal tract contains another transport system for β-alanine namely the H + -coupled amino acid transporter SLC36A1 which is also known variously as system PAT, PAT1 or the imino acid carrier (Thwaites et al. 1993;Chen et al. 2003;Anderson et al. 2004;Thwaites & Anderson, 2007). To reduce confusion in the literature, the term β-alanine carrier should be avoided and the names SLC6A14 and ATB •,+ adopted to be consistent with descriptions in other tissues (Van Winkle et al. 1985;Munck & Munck, 1994, 1995Sloan & Mager, 1999;Sloan et al. 2003).


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Nedd4-2 Induces Endocytosis and Degradation of Proteolytically Cleaved Epithelial Na+ Channels*

As a pathway for Na+ reabsorption, the epithelial Na+ channel ENaC is critical for Na+ homeostasis and blood pressure control. Na+ transport is regulated by Nedd4-2, an E3 ubiquitin ligase that decreases ENaC expression at the cell surface. To investigate the underlying mechanisms, we proteolytically cleaved/activated ENaC at the cell surface and then quantitated the rate of disappearance of cleaved channels using electrophysiological and biochemical assays. We found that cleaved ENaC channels were rapidly removed from the cell surface. Deletion or mutation of the Nedd4-2 binding motifs in α, β, and γENaC dramatically reduced endocytosis, whereas a mutation that disrupts a YXXØ endocytosis motif had no effect. ENaC endocytosis was also decreased by silencing of Nedd4-2 and by expression of a dominant negative Nedd4-2 construct. Conversely, Nedd4-2 overexpression increased ENaC endocytosis in human embryonic kidney 293 cells but had no effect in Fischer rat thyroid epithelia. In addition to its effect on endocytosis, Nedd4-2 also increased the rate of degradation of the cell surface pool of cleaved αENaC. Together the data indicate that Nedd4-2 reduces ENaC surface expression by altering its trafficking at two distinct sites in the endocytic pathway, inducing endocytosis of cleaved channels and targeting them for degradation.

also modulated by aldosterone and vasopressin via serum and glucocorticoid-regulated kinase and protein kinase A, respectively; both kinases phosphorylate Nedd4-2, which reduces its binding to ENaC (6,12,13).
However, the mechanism by which Nedd4-2 reduces ENaC surface expression is uncertain. It is possible that Nedd4-2 regulates ENaC trafficking in the biosynthetic pathway, targeting it for degradation in the proteasome. Consistent with this model, localization of Nedd4-2 at the cell surface is not required for Nedd4-2 to inhibit ENaC (14). Moreover, proteasome inhibitors decrease ENaC degradation (15)(16)(17) and increase ENaC surface expression. 2 Alternatively, Nedd4-2 could regulate ENaC in the endocytic pathway, altering ENaC endocytosis and/or targeting to lysosomes for degradation. This model is suggested by recent data from our laboratory and others indicating that Nedd4-2 binds to ENaC at the cell surface, where it catalyzes ubiquitination of each ENaC subunit (18,19).
In this work, we investigated the mechanism(s) by which Nedd4-2 reduces ENaC surface expression. To overcome technical hurdles that have hindered progress in this area, we developed a novel strategy; we took advantage of the observation that ENaC is activated by proteolytic cleavage at specific sites in the extracellular domains of the ␣ and ␥ subunits (20 -23). Using electrophysiological and biochemical assays, we tested the effect of Nedd4-2 on endocytosis and degradation of proteolytically cleaved channels.
Electrophysiological Endocytosis Assay-Fischer rat thyroid (FRT) cells cultured on permeable filter supports were transfected (TFX50; Promega) (12) with the following human ENaC subunits; ␣ or ␣ Cl-1 (R177A, R178A), ␤, and ␥ or ␥ Cl (R135A, R137A, R138A, R178W, R180A, K181A). For overexpression experiments, the cells were cotransfected with 0.23 g of each ENaC subunit along with either green fluorescent protein * The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. 1 To whom correspondence should be addressed: 371 EMRB, University of Iowa College of Medicine, Iowa City, IA 52242. E-mail: peter-snyder@ uiowa.edu.
(GFP, control) or Nedd4-2 (0.3 g). For RNA interference experiments, cells were cotransfected with 0.27 g of each ENaC subunit and siRNA against GFP (control) or Nedd4-2 (0.2 g) (26). In some studies, ENaC subunits contained the following mutations: ␣ Y644A , ␤ R566X , ␤ Y620A , ␤ P616 -618A , ␥ Y627A , or ␥ T629A . Following transfection, the cells were cultured for 48 h as described previously (12). Short circuit current was measured using modified Ussing chambers (Warner Instrument Corp.). The apical and basolateral surfaces were bathed in 135 mM NaCl, 1.2 mM CaCl 2 , 1.2 mM MgCl 2 , 2.4 mM K 2 HPO 4 , 0.6 mM KH 2 PO 4 , 10 mM HEPES, pH 7.4, at 37°C. Amiloride-sensitive short circuit current was determined as the current difference with and without amiloride (10 M) in the apical bathing solution. To proteolytically cleave and activate ENaC at the cell surface, trypsin (10 g/ml) was added to the apical membrane for 10 min and then removed by vigorous washes with ϳ12 times the volume of the apical chamber. Amiloride-sensitive current was measured every 5 min by addition of amiloride (10 M) to the apical membrane followed by wash out of amiloride.
Degradation Assay-HEK 293T cells were transfected with ␣-FLAG, ␤, and ␥ENaC with Nedd4-2 or GFP. 48 h later, cells were biotinylated as above and then incubated at 37°C for times between 0 and 80 min. Following lysis of the cells in Nonidet P-40 lysis buffer, biotinylated ␣ENaC was isolated with Neutr-Avidin beads, separated by SDS-PAGE, and detected by immu-noblot (anti-FLAG M2 monoclonal antibody-peroxidase conjugate). Fig. 1A, we transfected FRT epithelia with ␣, ␤, and ␥ENaC and measured the short circuit current blocked by amiloride as an assay of ENaC activity. ENaC activity requires proteolytic cleavage of the extracellular domains of the ␣ and ␥ subunits. The basal amiloride-sensitive current (Fig. 1A) reflects ENaC channels cleaved in the biosynthetic pathway (27,28). Addition of trypsin to the extracellular solution increased amiloride-sensitive current 2-fold, reflecting acute proteolytic cleavage/activation of a pool of uncleaved (inactive) channels at the cell surface (Fig.  1A). This finding is consistent with previous work (7,23,27). In Fig. 1B, we mutated a consensus site for cleavage by furin in ␣ENaC (␣ Cl ; R177A/178A), and in ␥ENaC we mutated sites (␥ Cl ) for furin (R135/137/138A) and CAP1 (R178W, K179A, R180A, K181A) (27,29). By preventing cleavage, these mutations nearly abolished basal amiloride-sensitive current. However, trypsin activated the mutant channel, generating a large amiloride-sensitive current. This presumably occurred via trypsin cleavage at remaining Arg or Lys residues adjacent to the mutated furin and CAP1 sites.

Proteolytic Cleavage of Cell Surface ENaC-In
Quantitation of Endocytosis of Proteolytically Cleaved ENaC-Expression of the ␣ Cl ␤␥ Cl mutant ENaC in FRT cells provided a strategy to measure the rate of ENaC endocytosis (Fig. 1C). A pool of channels at the cell surface is proteolytically cleaved and activated with a brief exposure to trypsin. Over time, cleaved/ active channels are removed from the cell surface by endocytosis, resulting in decreased amiloride-sensitive current. The rate of decrease in current reflects the rate of ENaC endocytosis. During this time course, newly synthesized channels also undergo exocytosis, but they are uncleaved/inactive and therefore do not contribute significantly to the current. Fig. 2A shows a representative current trace. Trypsin activated a large amiloride-sensitive current (arrowheads indicate A and B, representative short circuit current traces in FRT epithelia transfected with ␣ENaC (wild-type or ␣ cl ), ␤ENaC, and ␥ENaC (wild-type or ␥ cl ) (0.33 g each). Amiloride (10 M) and trypsin (2 g/ml) were added to apical bathing solution as indicated. C, model showing strategy for endocytosis assay. Uncleaved ENaC at the cell surface is cleaved by trypsin, which activates the channel. The rate of disappearance of cleaved channels from the cell surface is quantitated as an assay of endocytosis.
brief addition of amiloride to quantitate ENaC current). Following removal of trypsin, amiloride-sensitive current decreased over time. Average data are shown in Fig. 2C, which is a plot of amiloride-sensitive current (relative to current immediately after trypsin removal) versus time after trypsin removal (error bars are hidden by the symbols), and data at 15 min are shown in Table 1. Current decreased rapidly over the first 15 min, followed by a much slower decrease. This suggests that cleaved ENaC is rapidly removed from the cell surface. The slower phase could represent a second more stable population of channels or could reflect recycling of cleaved channels back to the cell surface, which would counter the decrease in current caused by endocytosis. Interestingly, re-addition of trypsin to the bathing solution generated a large increase in amiloridesensitive current. This likely reflects previously uncleaved/inactive channels inserted into the plasma membrane during the 45-min interval following the initial trypsin exposure.
Liddle Syndrome Mutations Decrease ENaC Endocytosis-Liddle syndrome mutations disrupt Nedd4-2 binding to ENaC by altering or deleting a C-terminal PY motif. To test the effect of Liddle syndrome mutations on ENaC endocytosis, we cotransfected FRT cells with ␣ Cl and ␥ Cl along with a mutant ␤ subunit. In Fig. 2, B and C, we tested ␤ R566X , which deletes most of the C terminus, including the PY motif. Following activation by trypsin, there was a gradual decline in amiloride-sensitive current. However, the rate of decrease was dramatically slower than for the wild-type ␤ subunit. The difference between the curves was mainly in the initial rapid phase, which was largely absent for ␤ R566X (Fig. 2C). In contrast, the curves for wild-type and ␤ R566X paralleled one another in the later phase. When trypsin was added to the bathing solution a second time, there was an increase in ENaC current, albeit much smaller than for wild-type ␤ENaC (Fig. 2B). Thus, Liddle syndrome mutations decrease ENaC exocytosis, consistent with previous work (30 -32).
In Fig. 2D, we tested a missense mutation within the ␤ENaC PY motif (␤ Y620A ) that also disrupts binding to Nedd4-2. This mutation slowed the rate of decrease in trypsin-activated ENaC current, similar to ␤ R566X . Equivalent mutations of the PY motifs in ␣ENaC (Y644A) and ␥ENaC (Y627A) also slowed the decline in current (Fig. 2, E and F) although, interestingly, mutation of the ␣ENaC PY motif had a smaller effect than the mutations in ␤ or ␥ENaC. Together, the data suggest that Liddle syndrome mutations decrease the rate of ENaC endocytosis.
Biochemical Endocytosis Assay-As a second strategy to quantitate ENaC endocytosis, we used a biochemical assay to measure the rate of removal of proteolytically cleaved channels from the cell surface. We coexpressed ␣, ␤, and ␥ENaC in HEK 293T cells; the ␣ subunit contained a FLAG epitope at the C terminus. To detect ␣ENaC at the cell surface, we biotinylated cell surface proteins, isolated them with NeutrAvidin beads, and then immunoblotted with anti-FLAG antibody. For wildtype ␣ENaC, we detected a 90-kDa band corresponding to the full-length protein and a 65-kDa band corresponding to the C-terminal cleavage fragment (Fig. 3A), consistent with previous work (7,33). To prevent cleavage by furin, we mutated the two furin consensus sites (␣ Cl-2 ), which has a similar effect on ENaC current as mutation of a single furin site (␣ Cl-1 ) (34). This eliminated the 65-kDa band (Fig. 3A). However, extracellular trypsin (5 g/ml for 5 min) cleaved ␣ Cl-2 , generating a 65-kDa band very similar in mass to the cleaved form of wild-type ␣ENaC (Fig. 3A). After removing trypsin from the extracellular medium, we measured the rate of disappearance of the 65-kDa band from the cell surface as an assay of ENaC endocytosis (Fig.   FIGURE 2. Electrophysiological endocytosis assay. FRT epithelia were cotransfected with ␣ Cl ENaC, ␤ENaC, and ␥ Cl ENaC (0.33 g each), and short circuit current was measured at 37°C. Liddle syndrome mutations were introduced in each ENaC subunit as indicated. A and B, representative current traces with wild-type (A) or R566X (B) ␤ENaC. Trypsin (10 g/ml, bars) and amiloride (10 M, arrowheads) were added to apical bathing solution as indicated. C-F, plots of trypsin-activated amiloride-sensitive current (relative to initial current after trypsin removal, I 0 , mean Ϯ S.E.) versus time after trypsin removal from the bathing solution. ENaC subunits contained the indicated mutations and were compared with wild-type ENaC studied on the same days. C, ␤ R566X (n ϭ 10); D, ␤ Y620A (n ϭ 8); E, ␣ Cl/Y644A (n ϭ 4); F, ␥ Cl/Y627A (n ϭ 4).

TABLE 1 ENaC endocytosis
Fraction of amiloride-sensitive current remaining (I/I 0 ) or fraction of proteolytically cleaved channels remaining at the cell surface (Cl/Cl 0 ) 5 or 15 min following removal of trypsin from the extracellular solution, as indicated (mean Ϯ S.E.). p values determined by t-test.  MARCH 7, 2008 • VOLUME 283 • NUMBER 10 1C shows model). Because newly synthesized channels undergoing exocytosis are 90 kDa, we were able to distinguish them from cleaved channels undergoing endocytosis. In Fig. 3B, top panel, we generated a pool of trypsin-cleaved ␣ Cl-2 -FLAG at the cell surface, incubated the cells at 37°C for 0 -60 min to allow endocytosis, and then biotinylated channels remaining at the cell surface. We observed a rapid decrease in the 65-kDa cleaved band at the cell surface (Fig. 3B, average data are quantitated in Fig. 3C); 50% was removed by 15 min and nearly all was removed at 60 min. Thus, the half-life of cleaved ␣ENaC at the cell surface was short (15 min). In contrast to the cleaved band, the quantity of the full-length 90-kDa band at the cell surface reflects the net contributions of both endocytosis and exocytosis of full-length ␣ENaC. The quantity of this band increased at 5 min (2.1 Ϯ 0.1-fold, n ϭ 3), likely resulting from exocytosis of newly synthesized channels. There was little change in the density of this band at later time points, indicating that a steady state between endocytosis and exocytosis was reestablished. As a control, there was no change in the quantity of ␣ Cl-2 -FLAG in the total cellular lysate during the course of the experiment (Fig. 3B, bottom panel). Minimal cleaved ␣ Cl-2 -FLAG was observed in the total lysate, indicating that only a small fraction of total ENaC in the cell was expressed at the cell surface, consistent with previous work (7).

Nedd4-2-induced Endocytosis and Degradation of ENaC
In Fig. 3B, right panels, and 3C, we tested the effect of Liddle syndrome mutations on endocytosis. Deletion of the C terminus of ␤ENaC (R566X) decreased the rate of disappearance of the cleaved 65-kDa band from the cell surface. At 15 min, there was no significant decrease in surface expression and the half-life lengthened to Ͼ60 min. Mutation of the PY motif (␤ Y620A ) had a similar effect (Fig. 3C). Together with the results of the electrophysiological assay, we conclude that proteolytically cleaved/active ENaC is rapidly removed from the cell surface and that Liddle syndrome mutations dramatically slow the rate of removal.
Nedd4-2 Binding Motif Mediates ENaC Endocytosis-The PPPXYXXL sequence mutated in Liddle syndrome fits the consensus for two motifs that have the potential to mediate ENaC endocytosis. First, it fits the YXXØ (Ø indicates hydrophobic amino acids) motif for endocytosis in clathrin-coated pits. This motif mediates endocytosis of the transferrin receptor (35). Second, it fits the PPXY PY motif consensus that binds to proteins containing WW domains, including Nedd4-2 (36). The Tyr (␤ Y620A ) is common to both motifs; mutation of this residue decreased ENaC endocytosis (Figs. 2D and 3C). Previous work indicates that the Leu contributes to WW domain binding and is also part of both motifs (37,38). To distinguish the relative contributions of these two motifs, we tested two additional mutations. Previous work indicates that mutation of a Thr within the sequence (␥ T629A ) disrupts the effect of a dominant negative dynamin cDNA (which blocks endocytosis via clathrin-coated pits) but does not alter its regulation by Nedd4-2 (39). Conversely, mutation of the three prolines (␤ P616 -618A ) prevents ENaC regulation by Nedd4-2 but does not disrupt clathrin-mediated endocytosis (39). We tested the effects of these mutations on ENaC endocytosis using both electrophysiological and biochemical assays. Compared with wild type, ␥ T629A did not alter the decline in trypsin-activated current (Fig. 4A) or the removal of the 65-kDa cleaved form of ␣ Cl-2 -FLAG from the cell surface (Fig. 4, B and C). In contrast, endocytosis was decreased by ␤ P616 -618A , similar to mutation of ␤ Y620 or deletion of the ␤ C terminus. These findings support a critical role for Nedd4-2 in mediating ENaC endocytosis. We cannot exclude a role for the YXXØ motif in regulating ENaC endocytosis in other cells.
Nedd4-2 Increases ENaC Endocytosis-As a more direct test of the role of Nedd4-2 in ENaC endocytosis, we transfected cells with Nedd4-2 siRNA. In previous work, we found that Nedd4-2 siRNA specifically silenced Nedd4-2 but not the related E3 ubiquitin ligase Nedd4 (26). Here we found that Nedd4-2 siRNA (compared with GFP siRNA) decreased the rate of removal of trypsin-activated channels from the cell surface in FRT epithelia, indicating a decrease in the rate of endocytosis (Fig. 5A). Likewise, Nedd4-2 siRNA reduced removal of cleaved ␣ Cl-2 -FLAG from the cell surface in HEK 293T cells (Fig. 5, B and C). As a second approach, we overexpressed a dominant negative form of Nedd4-2 that contains the four WW domains that bind to ENaC but lacks the HECT domain that catalyzes ENaC ubiquitination (7). The dominant negative Nedd4-2 also decreased removal of cleaved channels from the cell surface (Fig. 5, B and C). Together, the data indicate that endogenous Nedd4-2 mediates ENaC endocytosis.
In Fig. 6, we tested the effect of Nedd4-2 overexpression on ENaC endocytosis. In HEK 293T cells, overexpression of Nedd4-2 increased endocytosis of cleaved channels (Fig. 6A). In contrast, overexpression did not alter the rate of ENaC endocytosis in FRT epithelia (Fig. 6B). . Biochemical endocytosis assay. HEK 293T cells were transfected with the following ENaC subunits; ␣-FLAG (wild-type or ␣ Cl-2 ), ␤ (wild-type, R566X, or Y620A), and ␥ (5.33 g each). 48 h after transfection, cells were treated with or without trypsin (5 g/ml for 5 min), and then cell surface ␣-FLAG was biotinylated, isolated with NeutrAvidin beads, and detected by immunoblot (anti-FLAG). A and B, representative immunoblots. In B, following removal of trypsin from the medium, cells were incubated for 0 -60 min at 37°C prior to biotinylation. Data are quantitated (densitometry) in C; plot of cleaved ␣-FLAG at the cell surface versus time at 37°C (relative to 0 min) (mean Ϯ S.E., n ϭ 3-8 for each data point). (40), where it can undergo one of two fates, recycling back to the cell surface (41) or degradation in lysosomes (15,31). We hypothesized that Nedd4-2 controls the fate of cleaved ENaC by targeting it for degradation. To test this hypothesis, we transfected HEK 293T cells with ␣-FLAG, ␤, and ␥ENaC, labeled ENaC at the cell surface with biotin (at 4°C), and then incubated the cells at 37°C for 0 -80 min. The disappearance of biotinylated ␣-FLAG reflects the degradation rate of the cell surface pool of ␣ENaC. In the absence of Nedd4-2, cell surface ␣ENaC was slowly degraded; Ͻ50% of the cleaved form was degraded at 80 min (Fig. 7, A and B). In contrast, Nedd4-2 dramatically increased degradation; Ͼ75% was degraded at 80 min (Fig. 7, A  and B). This finding is similar to our previous work with ␤ENaC (18). Nedd4-2 also increased degradation of the full-length form of ␣ENaC (Fig. 7, A and B). Together the data suggest that Nedd4-2 reduces surface expression of cleaved ENaC by increasing both its endocytosis and its degradation.

Nedd4-2-induced Endocytosis and Degradation of ENaC
In contrast to this lack of effect of Nedd4-2 overexpression on ENaC endocytosis in FRT epithelia, our previous work found that Nedd4-2 overexpression decreased ENaC current in these cells (12). This indicates that increased endocytosis is not the sole mechanism by which Nedd4-2 regulates ENaC. Consistent with this conclusion, we found that Nedd4-2 overexpression increased degradation of the cell surface fraction of ENaC. The data support a model in which Nedd4-2 regulates ENaC at two distinct sites in the endocytic pathway. First, Nedd4-2 increases ENaC endocytosis from the cell surface into endosomes. This step is rapid, occurring over 5-15 min (depending on levels of Nedd4-2). Second, once in endosomes, Nedd4-2 targets ENaC for degradation in lysosomes, decreasing the ENaC pool available for recycling back to the cell surface. This is consistent with the recent report that a Liddle syndrome mutant decreased ENaC colocalization with a lysosomal marker (31). The net effect of both is to reduce the expression of ENaC at the cell surface and, hence, decrease epithelial Na ϩ transport.
Previous studies have reported a half-life for removal of ENaC from the cell surface ranging from 30 min to 3.6 h (31,32,(42)(43)(44). The half-life that we observed was shorter; a rapid phase of endocytosis occurred over 15 min in FRT cells and in HEK 293 cells the t1 ⁄ 2 for endocytosis was 15 min. This difference, as well as the wide variability in previous reports, could be explained by methodological differences. In each of the previous reports, the strategy was to inhibit protein synthesis (cycloheximide) or disrupt the Golgi (brefeldin A) and then measure decay of ENaC current or surface expression. These drugs have also been used to show that current decay is slowed by Liddle syndrome mutations (31,32,42). One limitation of this strategy is the significant (and unknown) time lag between addition of the drug and depletion of the biosynthetic pool of ENaC available for insertion into the plasma membrane. A recent study suggested that this pool was depleted very slowly following addition of cycloheximide in Madin-Darby canine kidney cells transfected with ENaC (31). This would lead to an underesti-mation of the endocytosis rate because the surface pool would be replenished by exocytosis of new channels. Moreover, cycloheximide and brefeldin A could inhibit synthesis/trafficking of a variety of proteins that mediate or regulate ENaC endocytosis. Rather than disrupt ENaC synthesis or trafficking, our strategy was to acutely modify a pool of channels at the cell surface (by proteolytic cleavage), which allowed us to follow the channels as they were removed from the surface using functional and biochemical assays. Somewhat analogous to a pulse-chase assay, this strategy has several advantages. Because of the discrete nature of the intervention, it provided improved time resolution compared with previous work. Moreover, the shift in molecular mass of ␣ENaC caused by cleavage allowed us to distinguish channels undergoing endocytosis from newly synthesized channels trafficking to the cell surface. In contrast to studies using brefeldin A or cycloheximide, our approach should not alter synthesis or exocytosis of proteins involved in ENaC trafficking, increasing specificity of the assay. Finally, this strategy allowed us to selectively quantitate endocytosis of the active (proteolytically cleaved) form of ENaC.
The strategy we used also requires assumptions. First, the electrophysiological assay assumes that there are no time-dependent changes in ENaC gating (i.e. rundown); decreased current could result if P O decreased over time. We think this is a good assumption, as we have not observed evidence of significant rundown in FRT epithelia. Moreover, the electrophysiological data were corroborated by a biochemical approach (biotinylation) that counted channel number, rather than activity. Second, the strategy assumes that channels cleaved by trypsin are endocytosed at the same rate as channels cleaved by endogenous proteases. Two observations support this assumption; trypsin and endogenous proteases generate ␣ENaC cleavage fragments that are very similar in size, and functionally they appear to cleave an overlapping set of residues (7,27). We do not yet know whether full-length/inactive channels are endocytosed at the same rate as cleaved/active channels. In fact, our previous work raised the interesting possibility that Nedd4-2 may selectively regulate trafficking of proteolytically cleaved channels, because it altered that ratio of cleaved to full-length channels at the cell surface (7). Additional work will be necessary to determine whether this change in ratio resulted from differences in endocytosis. Third, the strategy assumes that the rate of endocytosis measured for ␣ENaC reflects endocytosis of functional ENaC channel complexes composed of all three subunits. In support of this assumption, we found that efficient expression of ␣ENaC at the cell surface in HEK 293T cells requires coexpression with ␤ and ␥ENaC, suggesting that the three subunits primarily traffic as a heteromultimeric complex in these cells. 4 Furthermore, the electrophysiological assay we used selectively quantitated endocytosis of functional channels; our previous work indicates that in FRT cells these channels are composed of all three ENaC subunits (30).
In FRT epithelia, ENaC endocytosis occurred over a biphasic time course. There are two potential explanations. First, there could be two or more distinct pools of ENaC with differing 4 R. Kabra, K. K. Knight, R. Zhou, and P. M. Snyder, unpublished observation. FIGURE 7. Nedd4-2 increases degradation of cell surface ENaC. HEK 293T cells were transfected with ␣-FLAG, ␤, and ␥ENaC subunits (1 g each) and either Nedd4-2 cDNA (ϩNedd4-2) or control GFP cDNA (ϪNedd4-2) (0.04 g). 48 h after transfection, the cells were biotinylated and then incubated for 0, 40, or 80 min at 37°C. Following lysis of the cells, biotinylated ␣-FLAG was isolated with NeutrAvidin beads and detected by immunoblot (anti-FLAG) (A), and the cleaved band was quantitated by densitometry (mean Ϯ S.E., n ϭ 4) (B). stability at the cell surface, one pool that is rapidly endocytosed and a second more stable pool. A variety of mechanisms could underlie this difference, including interactions with associated proteins that modulate endocytosis or localization in membrane microdomains with differing turnover rates. Second, the slower component could reflect recycling of endocytosed trypsin-activated channels late in the time course of the experiment, which would reduce the apparent rate of endocytosis. Our data certainly do not exclude a role for Nedd4-2 in the regulation of ENaC recycling. Although not the primary purpose of the current study, we observed a decrease in ENaC exocytosis when the channel contained a mutation in the Nedd4-2 binding sequence (PY motif, Fig. 2, A and B). However, based on trypsin sensitivity, this did not appear to arise from recycling of channels but reflected a pool of newly synthesized (trypsin-sensitive) channels. This finding is consistent with previous work from our laboratory and others (30 -32).
Elucidating the mechanisms by which Nedd4-2 regulates ENaC surface expression is important for our understanding of Na ϩ homeostasis and the pathogenesis of disease. Nedd4-2 is a critical convergence point for the regulation of epithelial Na ϩ transport. By decreasing the expression of ENaC at the cell surface, Nedd4-2 reduces Na ϩ reabsorption to maintain Na ϩ homeostasis. Defects in this regulation cause Liddle syndrome, an inherited form of hypertension. Moreover, single nucleotide polymorphisms in Nedd4-2 have been linked to hypertension (45), raising the intriguing possibility that Nedd4-2 may play a role in more common forms of hypertension. Our findings, together with previous work, focus attention on the endocytic pathway for identification of new candidate genes and potential therapeutic targets for hypertension and other diseases of Na ϩ homeostasis.